Menaker T, Zamansky A, van der Linden D, et al. Towards a Methodology for Data-Driven Automatic Analysis of Animal Behavioral Patterns. ACI '20: Proceedings of the Seventh International Conference on Animal-Computer Interaction. 2021;12:1-6. https://doi.org/10.1145/3446002.3446126.
This study proposes a data-driven framework to guide researchers in selecting relevant behavioral parameters for animal behavior analysis, particularly in automated detection and tracking systems. The framework employs data mining techniques to extract insights from experimental data, aiding in the identification of key parameters without prior assumptions. A clustering-based analysis of animal trajectories is used to demonstrate the method, identifying "prevalent areas of stay" in experimental settings. The methodology aims to address the challenge of parameter selection in behavior studies, particularly in the context of increasing automation in animal-computer interaction research.
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